[go: up one dir, main page]

WO2016205627A1 - Contrôle en retour à base d'irm d'un fractionnement mécanique à base d'ultrasons de tissus biologiques - Google Patents

Contrôle en retour à base d'irm d'un fractionnement mécanique à base d'ultrasons de tissus biologiques Download PDF

Info

Publication number
WO2016205627A1
WO2016205627A1 PCT/US2016/038052 US2016038052W WO2016205627A1 WO 2016205627 A1 WO2016205627 A1 WO 2016205627A1 US 2016038052 W US2016038052 W US 2016038052W WO 2016205627 A1 WO2016205627 A1 WO 2016205627A1
Authority
WO
WIPO (PCT)
Prior art keywords
mri data
parameters
biological tissue
computer readable
readable medium
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/US2016/038052
Other languages
English (en)
Inventor
Ari Partanen
Wayne Kreider
Vera KHOKHLOVA
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Individual
Original Assignee
Individual
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Individual filed Critical Individual
Priority to US15/737,670 priority Critical patent/US11224356B2/en
Publication of WO2016205627A1 publication Critical patent/WO2016205627A1/fr
Anticipated expiration legal-status Critical
Priority to US17/543,276 priority patent/US12396653B2/en
Ceased legal-status Critical Current

Links

Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/05Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
    • A61B5/055Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/0033Features or image-related aspects of imaging apparatus, e.g. for MRI, optical tomography or impedance tomography apparatus; Arrangements of imaging apparatus in a room
    • A61B5/0035Features or image-related aspects of imaging apparatus, e.g. for MRI, optical tomography or impedance tomography apparatus; Arrangements of imaging apparatus in a room adapted for acquisition of images from more than one imaging mode, e.g. combining MRI and optical tomography
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/01Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61NELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N7/00Ultrasound therapy
    • A61N7/02Localised ultrasound hyperthermia
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00Arrangements or instruments for measuring magnetic variables
    • G01R33/20Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/44Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
    • G01R33/48NMR imaging systems
    • G01R33/4808Multimodal MR, e.g. MR combined with positron emission tomography [PET], MR combined with ultrasound or MR combined with computed tomography [CT]
    • G01R33/4814MR combined with ultrasound
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00Arrangements or instruments for measuring magnetic variables
    • G01R33/20Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/44Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
    • G01R33/48NMR imaging systems
    • G01R33/54Signal processing systems, e.g. using pulse sequences ; Generation or control of pulse sequences; Operator console
    • G01R33/56Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution
    • G01R33/5602Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution by filtering or weighting based on different relaxation times within the sample, e.g. T1 weighting using an inversion pulse
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00Arrangements or instruments for measuring magnetic variables
    • G01R33/20Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/44Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
    • G01R33/48NMR imaging systems
    • G01R33/54Signal processing systems, e.g. using pulse sequences ; Generation or control of pulse sequences; Operator console
    • G01R33/56Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution
    • G01R33/563Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution of moving material, e.g. flow contrast angiography
    • G01R33/56341Diffusion imaging
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B90/00Instruments, implements or accessories specially adapted for surgery or diagnosis and not covered by any of the groups A61B1/00 - A61B50/00, e.g. for luxation treatment or for protecting wound edges
    • A61B90/36Image-producing devices or illumination devices not otherwise provided for
    • A61B90/37Surgical systems with images on a monitor during operation
    • A61B2090/374NMR or MRI
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61NELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N7/00Ultrasound therapy
    • A61N2007/0056Beam shaping elements
    • A61N2007/006Lenses
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61NELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N7/00Ultrasound therapy
    • A61N2007/0056Beam shaping elements
    • A61N2007/0065Concave transducers
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61NELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N7/00Ultrasound therapy
    • A61N2007/0082Scanning transducers
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00Arrangements or instruments for measuring magnetic variables
    • G01R33/20Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/44Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
    • G01R33/48NMR imaging systems
    • G01R33/50NMR imaging systems based on the determination of relaxation times, e.g. T1 measurement by IR sequences; T2 measurement by multiple-echo sequences
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00Arrangements or instruments for measuring magnetic variables
    • G01R33/20Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/44Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
    • G01R33/48NMR imaging systems
    • G01R33/54Signal processing systems, e.g. using pulse sequences ; Generation or control of pulse sequences; Operator console
    • G01R33/56Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution
    • G01R33/563Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution of moving material, e.g. flow contrast angiography
    • G01R33/56358Elastography

Definitions

  • High intensity focused ultrasound is a medical technology capable of transcutaneously fractionating or ablating selected portions of tissue without damaging intervening or surrounding tissues.
  • tissue is thermally ablated via heating caused by ultrasound energy absorption.
  • HIFU waves to fractionate, ablate, damage, or disintegrate diseased biological tissue or a foreign object within a patient. More specifically, energy carried by HIFU waves may be absorbed by a target region of tissue or absorbed by an object, so that the temperature of the target region or object is increased, causing thermal ablation.
  • HIFU waves can also be sequentially focused (e.g., deflected or scanned) upon different target regions so that a larger macroscopic region of tissue or a large object may be thermally ablated.
  • Techniques for HIFU-induced mechanical fractionation exist as well.
  • a method includes displaying, via a user interface, an image representing first magnetic resonance imaging (MRI) data corresponding to biological tissue.
  • the method further includes receiving, via the user interface, first input identifying one or more target regions of the biological tissue to be mechanically fractionated via exposure to first ultrasound waves.
  • the method further includes applying the first ultrasound waves to the one or more target regions, thereby mechanically fractionating at least a portion of the one or more target regions.
  • the first ultrasound waves are applied according to one or more first parameters.
  • the method further includes, contemporaneous to or after applying the first ultrasound waves, acquiring second MRI data corresponding to the biological tissue.
  • the method further includes determining, based on the second MRI data, one or more second parameters for applying second ultrasound waves to the biological tissue.
  • the method further includes applying the second ultrasound waves to the biological tissue according to the one or more second parameters.
  • a non-transitory computer readable medium stores instructions that, when executed by a device, cause the device to perform functions.
  • the functions include displaying, via a user interface of the device, an image representing first magnetic resonance imaging (MRI) data corresponding to biological tissue.
  • the functions further include receiving, via the user interface, first input identifying one or more target regions of the biological tissue to be mechanically fractionated via exposure to first ultrasound waves.
  • the functions further include applying, via a transducer of the device, the first ultrasound waves to the one or more target regions, thereby mechanically fractionating at least a portion of the one or more target regions.
  • the first ultrasound waves are applied according to one or more first parameters.
  • the functions further include, contemporaneous to or after applying the first ultrasound waves, acquiring, via an MRI imaging system of the device, second MRI data corresponding to the biological tissue.
  • the functions further include determining, based on the second MRI data, one or more second parameters for applying second ultrasound waves to the biological tissue.
  • the functions further include applying, via the transducer, the second ultrasound waves to the biological tissue according to the one or more second parameters.
  • a device includes one or more processors, a user interface, a transducer, a magnetic resonance imaging (MRI) system, and a non-transitory computer readable medium storing instructions that, when executed by the one or more processors, cause the device to perform functions.
  • the functions include displaying, via the user interface, an image representing first MRI data corresponding to biological tissue.
  • the functions further include receiving, via the user interface, first input identifying one or more target regions of the biological tissue to be mechanically fractionated via exposure to first ultrasound waves.
  • the functions further include applying, via the transducer, the first ultrasound waves to the one or more target regions, thereby mechanically fractionating at least a portion of the one or more target regions.
  • the first ultrasound waves are applied according to one or more first parameters.
  • the functions further include, contemporaneous to or after applying the first ultrasound waves, acquiring, via the MRI imaging system, second MRI data corresponding to the biological tissue.
  • the functions further include determining, based on the second MRI data, one or more second parameters for applying second ultrasound waves to the biological tissue.
  • the functions further include applying, via the transducer, the second ultrasound waves to the biological tissue according to the one or more second parameters.
  • Figure 1 is a schematic diagram of a device configured for mechanical fractionation of biological tissue or other objects, in accordance with example embodiments.
  • Figure 2 is a flow chart depicting an example method for mechanical fractionation of a volume within biological tissue or other objects, in accordance with example embodiments.
  • Figure 3 is a simplified depiction of an image of biological tissue displayed by a user interface, in accordance with example embodiments.
  • Figure 4 is a simplified depiction of an image of biological tissue with target regions that have been selected for mechanical fractionation, in accordance with example embodiments.
  • Figure 5 is an illustration of emitted ultrasound pulses defined by several parameters, in accordance with example embodiments.
  • Figure 6 is a simplified depiction of an image of biological tissue that has undergone a portion of a mechanical fractionation procedure, in accordance with example embodiments.
  • Figure 7 is a simplified depiction of an image of biological tissue with avoidance regions that have been selected for monitoring during mechanical fractionation of target regions, in accordance with example embodiments.
  • Figure 8A is a T2-weighted MRI image of ex vivo bovine liver tissue in the coronal image plane with target regions shown.
  • Figure 8B is a T2-weighted MRI image of ex vivo bovine liver tissue in the sagittal image plane with target regions shown.
  • Figure 9 is a real-time temperature map of ex vivo bovine liver tissue in the coronal plane.
  • Figure 10 is a graph depicting temperature over time for a region of the ex vivo bovine liver tissue.
  • Figure 11A is a real-time fast-field-echo (FFE) image of the ex vivo bovine liver tissue in the coronal plane.
  • FFE fast-field-echo
  • Figure 1 IB is a real-time FFE image of the ex vivo bovine liver tissue in the sagittal plane.
  • Figure 12A is a real-time FFE image of the ex vivo bovine liver tissue showing one volumetric soni cation.
  • Figure 12B is a real-time FFE image of the ex vivo bovine liver tissue showing two volumetric sonications.
  • Figure 12C is a real-time FFE image of the ex vivo bovine liver tissue showing three volumetric sonications.
  • Figure 12D is a real-time FFE image of the ex vivo bovine liver tissue showing four volumetric sonications.
  • Figure 13 A is an FFE image of ex vivo bovine liver tissue after a first sonication.
  • Figure 13B is an FFE image of the ex vivo bovine liver tissue during a second sonication.
  • Figure 13C is an FFE image of the ex vivo bovine liver tissue after the second sonication.
  • Figure 14 is a T2-weighted image of the ex vivo bovine liver tissue after the completion of a sonication therapy.
  • MRI magnetic resonance imaging
  • MR diagnostic techniques can be used in conventional HIFU therapy
  • the purely thermal nature of conventional HIFU can limit the utility of MRI and MR techniques for monitoring, control, and diagnostic evaluation of HIFU when applied clinically or even experimentally.
  • the limitations are largely due to diffusion of heat within biological tissue undergoing HIFU sonication.
  • diffusion of absorbed heat outward from a focal point of the HIFU sonication may render lesion formation somewhat imprecise and/or unpredictable.
  • the boundary between thermally ablated biological tissue and undisturbed tissue may drift outward from its intended location.
  • the boundary itself may lack sharpness, forming instead a possibly undesirable gradual transition from fully ablated tissue to undisturbed tissue surrounding the ablated tissue.
  • the volumetric extent of lesion formation may not be known until some time after HIFU sonication ceases. This can limit the utility of MRI and MR techniques for real-time monitoring of the effects of HIFU during sonication; the viability of evaluating the final lesion size may be similarly constrained.
  • an example method includes displaying, via a user interface, an image representing first magnetic resonance imaging (MRI) data corresponding to biological tissue.
  • the method further includes receiving, via the user interface, first input identifying one or more target regions of the biological tissue to be mechanically fractionated via exposure to first ultrasound waves.
  • the method further includes applying the first ultrasound waves to the one or more target regions, thereby mechanically fractionating at least a portion of the one or more target regions.
  • the first ultrasound waves may be applied according to one or more first parameters.
  • the method further includes, contemporaneous to or after applying the first ultrasound waves, acquiring second MRI data corresponding to the biological tissue.
  • the method further includes determining, based on the second MRI data, one or more second parameters for applying second ultrasound waves to the biological tissue.
  • the method further includes applying the second ultrasound waves to the biological tissue according to the one or more second parameters.
  • HIFU may be adapted to cause targeted and controlled destruction of biological tissue by mechanical fractionation instead of by pure thermal ablation.
  • This mechanical fractionation technique may enable destruction of one or more target regions of biological tissue with improved control.
  • the technique may enable better control of the size and shape of the ablated portion of tissue, and better control of the location and definition of the boundary between ablated and non-ablated tissue. Post-sonication heat diffusion can typically be better managed via this mechanical fractionation technique.
  • an adapted HIFU technique termed “boiling histotripsy” is used for generating mechanically fractionated lesions in biological tissue.
  • BH is a therapeutic technique in which lesions can be purely mechanical in origin, i.e. liquefied, or, in addition to mechanical fractionation, include different degrees of thermal effect controlled by the parameters of an ultrasound exposure (sonication) protocol. Specifically, the peak output power, resultant in situ shock amplitude, ultrasound frequency, pulse length, pulse repetition rate, number of pulses, and sonication trajectory can be adjusted.
  • BH sonication was performed volumetrically, i.e., involving concurrently or sequentially sonicating regions larger than a single focal point.
  • various MRI methods were used to monitor BH sonication in real time, as well as assess the therapy outcome.
  • MRI can provide in vivo anatomical, functional, and temperature images, as well as provide information on tissue displacement in real time during a HIFU sonication. While MRI-based feedback can be used to control conventional MR-HIFU thermal ablation, (e.g., to achieve complete thermal necrosis in the target region), as well as to control conventional MR-HIFU mediated mild hyperthermia, these techniques rely on the monitoring of HIFU- induced temperature changes only.
  • the BH method can be used to induce mechanically-fractionated lesions with a controlled degree of thermal effect.
  • the technique may involve repetitive millisecond-long pulses with shocks, rapid localized boiling in tissue caused by shock wave heating, and interaction of shocks with a vapor cavity.
  • shocks rapid localized boiling in tissue caused by shock wave heating
  • interaction of shocks with a vapor cavity Such an approach can be advantageous for avoiding overheating of vessels, bone, or other structures located close to the treatment site.
  • This approach may also accelerate resorption or passage of the ablated tissue volume, diminish pressure on the surrounding organs that causes discomfort, and insert openings between tissues, among other desired effects or outcomes.
  • Some benefits enabled by BH are the ability to use MRI to accurately plan BH- sonications, to perform BH-therapy under real-time imaging guidance, and to evaluate the outcome of the treatment.
  • thermally coagulated region may be estimated based on accumulated thermal dose, and might not accurately reflect the final post- therapy outcome.
  • temperature in the target region may be elevated to 40-45° C for a prolonged duration, after which the tissue is allowed to cool down.
  • the region of mild hyperthermia may be estimated from the temperature gradients and/or thermal dose over time.
  • tissue contrast changes are not easily seen via MR-imaging when used in conjunction with either thermal ablation or mild hyperthermia.
  • various MRI methods can be used during BH-mediated mechanical tissue fractionation to monitor and control progress of BH in real time based on tissue contrast changes.
  • real-time imaging findings can provide a basis for adjusting the sonication power, duty cycle, duration, number of pulses, and/or sonication trajectory for more desirable results (e.g., full mechanical fractionation of tissue at the target location).
  • temperature can be monitored simultaneously inside and outside of the target region to avoid exceedingly high temperatures at the target as well as avoid temperature elevations and tissue damage outside of the target region.
  • MRI- assisted BH Use of MRI and MR techniques in conjunction with BH (and HIFU histotripsy in general) to plan, monitor, control, and evaluate BH-induced targeted destruction of biological tissue prior to, during, and after BH sonication is referred to herein as "MRI- assisted BH.”
  • biological tissue is used herein to refer generically to tissue such as human (or other animal) tissue and/or organs, as well as other tissue of biological origin.
  • Biological tissue human or other
  • Biological tissue can be part of a living or non-living subject.
  • demonstration operations of MRI-assisted BH were applied to sample biological tissue including ex vivo bovine liver and heart tissue.
  • Other non-limiting examples of "biological tissue” used herein include liver tissue, uterine tissue, kidney tissue, prostate tissue, thyroid tissue, pancreas tissue, brain tissue, nerve tissue, connective tissue, fat tissue, or muscle tissue.
  • Biological tissue can also include a biological substance, such as a blood clot or a hematoma.
  • MRI-assisted BH can be applied to treatment of pathological tissue, such as malignant tumors and/or benign tumors, where non-limiting examples of benign tumors include an adenoma or a fibroid. Additionally, MRI-assisted BH can used to create and/or insert of openings in biological tissue for various therapeutic purposes.
  • Figure 1 illustrates an example device (or system) 100 configured to mechanically fractionate biological tissue 114 (or other objects) using an acoustic ultrasound wave (or "HIFU" wave) 113.
  • the device 100 includes one or more processors 102, data storage 104, a user interface 106, a signal generator 108, an ultrasound transducer 110, and a magnetic resonance imaging (MRI) system 116, any or all of which may be communicatively coupled to each other via a system bus or another connection mechanism 112.
  • processors 102 data storage 104
  • data storage 104 includes one or more processors 102, data storage 104, a user interface 106, a signal generator 108, an ultrasound transducer 110, and a magnetic resonance imaging (MRI) system 116, any or all of which may be communicatively coupled to each other via a system bus or another connection mechanism 112.
  • MRI magnetic resonance imaging
  • the processor(s) 102 may include a general purpose processor and/or a special purpose processor and may be configured to execute program instructions stored within data storage 104.
  • the processor(s) 102 may be a multi-core processor comprised of one or more processing units configured to coordinate to execute instructions stored within data storage 104.
  • the processor(s) 102 by executing program instructions stored within data storage 104, may provide ultrasound parameters to the signal generator 108 for generation of ultrasound waves.
  • the processor(s) 102 may provide, to the signal generator 108, ultrasound parameters that are received via the user interface 106.
  • Data storage 104 may include one or more volatile, non-volatile, removable, and/or non-removable storage components.
  • Data storage 104 may include a magnetic, optical, or flash storage medium, and may be integrated in whole or in part with the processor(s) 102 or other portions of the device 100. Further, the data storage 104 may be a non-transitory computer-readable storage medium, having stored thereon program instructions that, when executed by the processor(s) 102, cause the device 100 to perform any function described in this disclosure. Such program instructions may be part of a software application that can be executed in response to inputs received from the user interface 106, for instance.
  • the data storage 104 may also store other types of information or data, such as those types described throughout this disclosure.
  • the user interface 106 may enable interaction with a user of the device 100, if applicable.
  • the user interface 106 may include input components such as a keyboard, a mouse, a keypad, a touchscreen, or a touch-sensitive panel, and output components such as a display screen (which, for example, may be combined with a touch-sensitive panel), a sound speaker, or a haptic feedback system.
  • the user interface 106 may receive input indicating various parameters for an ultrasound wave to be generated by the ultrasound transducer 110.
  • the signal generator 108 may be configured to receive, from the processor(s) 102, data indicative of ultrasound parameters for generation of an ultrasound wave by the ultrasound transducer 110.
  • the processor(s) 102 may send, to the signal generator 108, data representative of input received via the user interface 106.
  • the received input may simply indicate one of several predetermined ultrasound fractionation protocols represented by program instructions stored at data storage 104.
  • the ultrasound fractionation protocols may be selected automatically by the processor(s) 102 based on MRI data received from the MRI imaging system 116.
  • Such data received by the signal generator 108 may indicate various ultrasound parameters such as power, power density, intensity, oscillation frequency, pulse duration, duty cycle, and a number of pulses to be generated for various portions of the biological tissue 114.
  • the received data may also indicate a trajectory, path, or sequence of portions of the biological tissue 114 upon which the focal point of the ultrasound wave may be sequentially directed upon.
  • multiple ultrasound beams may be focused on multiple regions of biologic tissue simultaneously.
  • the received data may also include timing information indicating when and/or for how long the focal point of the ultrasound wave should be directed upon each respective portion of the biological tissue 114.
  • the ultrasound transducer 110 may include an array of one or more piezoelectric transducer elements or a lithotripter configured to generate ultrasound or other acoustic waves in response to receiving control signals representing ultrasound parameters from the signal generator 108.
  • the ultrasound transducer 110 may include a phased array of transducer elements configured to electronically focus or steer a generated ultrasound wave upon various portions of the biological tissue 114 via constructive and/or destructive wave interference.
  • Each transducer element of the ultrasound transducer 110 may receive its own independent control signal from the signal generator 108.
  • the signal generator 108 and the ultrasound transducer 110 may be integrated into one functional unit.
  • the ultrasound transducer 110 may include one or more of (i) a lens, (ii) one or more transducers having a radius of curvature at the focal point of the ultrasound wave, and (iii) a phased array of transducers.
  • Some examples of forms the biological tissue 114 may take include a tumor, a hematoma, an abscess, a lipoma, or any other diseased or undesirable tissue.
  • the biological tissue may also include any combination of one or more of the following types of tissues: liver, uterus, kidney, prostate, brain, breast, heart, blood vessel, lung, fat, nerve, or pancreas. Other examples are possible.
  • the device 100 may be used to fractionate any object or tissue. It should be assumed that for any example disclosed herein involving biological tissue, a generic object may be substituted in place of the biological tissue. In these examples, the object might take the form of a foreign object within a living body, but other examples are possible.
  • the MRI Imaging system 116 may include superconductive magnets, gradient coils, and/or RF transmission and reception coils, among other components.
  • the MRI imaging system 116 may take the form of a Philips Achieva 3T clinical MR scanner. In other examples, the MRI imaging system 116 may take the following forms as well: Philips Ingenia, Philips Multiva, Siemens Magnetom, GE Signa, GE Optima, GE Discovery, Toshiba Vantage, Hitachi Echelon, or Hitachi Oasis. Other examples are possible.
  • the MRI imaging system 116 may be configured to use the superconductive magnets (or other means) to apply a static magnetic field to biological tissue or other material under examination.
  • the static magnetic field may align the spin of many or most hydrogen nuclei (i.e., protons) within the biological tissue to be parallel with a single axis. (Nuclei of atoms other than hydrogen may be imaged as well.)
  • the transmission coils (or other means) may be used to apply a time-varying (e.g., RF) magnetic field, thereby realigning the spins of at least some of the hydrogen nuclei away from the axis of the static field.
  • RF time-varying
  • the reception coils or other means
  • images can be generated by the MRI imaging system 116 and displayed by the user interface 106.
  • Figure 2 is a flow chart depicting an example method 200 for mechanically fractionating biological tissue or other objects.
  • the method 200 depicted in Figure 2 presents an example method that can be performed using the device 100.
  • the method 200 may be performed via any combination of suitable components described herein.
  • Figure 2 may include one or more operations, functions, or actions as illustrated by one or more of blocks 202, 204, 206, 208, 210, and 212. Although the blocks are illustrated in a sequential order, these blocks may in some instances be performed in parallel, and/or in a different order than those described herein. Also, the various blocks may be combined into fewer blocks, divided into additional blocks, and/or removed based upon the desired implementation.
  • each block may represent a module, a segment, or a portion of program code, which includes one or more instructions executable by a processor for implementing specific logical functions or steps in a process.
  • the program code may be stored on any type of computer readable medium, for example, such as a storage device including a disk or hard drive.
  • the computer readable medium may include a non-transitory computer readable medium, for example, such as computer readable media that stores data for short periods of time like register memory, processor cache, or Random Access Memory (RAM).
  • the computer readable medium may also include non-transitory media, such as secondary or persistent long term storage, like read-only memory (ROM), optical or magnetic disks, or compact-disc read-only memory (CD-ROM), for example.
  • the computer readable media may also be any other volatile or non-volatile storage system.
  • the computer readable medium may be considered a computer readable storage medium, a tangible storage device, or other article of manufacture, for example.
  • each block in Figure 2 may represent circuitry that is wired to perform the specific logical functions in the process.
  • the method 200 involves displaying, via a user interface, an image representing first magnetic resonance imaging (MRI) data corresponding to biological tissue.
  • MRI magnetic resonance imaging
  • the user interface 106 may display an image 360 representing first MRI data corresponding to the biological tissue 114.
  • the MRI imaging system 116 may acquire the first MRI data depicted by the image 360.
  • the first MRI data may be acquired by the MRI imaging system 116 or another MRI system during a previous imaging session.
  • the image 360 i.e., the biological tissue 114) is arbitrarily apportioned into regions 301-350 for the purpose of explaining concepts below.
  • the first MRI data may include any combination of one or more of the following: diffusion-weighted MRI data, tissue elasticity data, temperature data, Tl-weighted data, T2- weighted data, proton density weighted data, magnetic resonance elastography (MRE) data, magnetic resonance acoustic radiation force imaging (MR-ARFI) data, Tl mapping data, T2 mapping data, contrast-enhanced MRI data, tissue displacement data, perfusion weighted imaging data, T2-star (T2*) weighted imaging data, T2* mapping imaging data, an apparent diffusion coefficient (ADC) map, or thermal dosage data.
  • the first MRI data may take other forms as well.
  • the method 200 involves receiving, via the user interface, first input identifying one or more target regions of the biological tissue to be mechanically fractionated via exposure to first ultrasound waves.
  • the user interface 106 may receive, via a mouse, touchscreen, or another user input device of the user interface 106, first input identifying portions 312, 313, 314, 322, 323, and 324 of the biological tissue 114 for mechanical fractionation, as indicated by shading in Figure 4.
  • mechanical fractionation may include processes in which ultrasound waves cause some degree of thermal ablation of the targeted tissue or object, although in many instances it will be beneficial if the damage inflicted on the targeted tissue or object is mostly mechanical in nature.
  • the first input itself may indicate the respective boundaries of the regions 312, 313, 314, 322, 323, and 324. For instance, a user might use a mouse or a touchscreen to encircle respective boundaries of the regions 312, 313, 314, 322, 323, and 324.
  • the first input might indicate a perimeter that collectively encircles the regions 312, 313, 314, 322, 323, and 324.
  • the first input may indicate a selection of a pre-defined boundary template whereby the first input also indicates positioning of the predefined boundary template upon the image 360.
  • the first input might take the form of a selection of a pre-defined rectangular boundary.
  • the first input might further indicate a size and a desired position of the pre-defined boundary (e.g, via a click and drag gesture).
  • the user- defined boundary might be circular or take other shapes as well.
  • the one or more target regions may, in practice, take the form of one or more target volumes. That is, the first input may indicate one or more three-dimensional regions for mechanical fractionation.
  • the user interface 106 may display images of the biological tissue 114 in more than one image plane to facilitate selection of three-dimensional volumes of the biological tissue 114.
  • the method 200 involves applying the first ultrasound waves to the one or more target regions, thereby mechanically fractionating at least a portion of the one or more target regions.
  • Mechanical fractionation may be intended to include physical effects such as liquification and/or deformation of tissues or objects, among other physical effects. Mechanical fractionation may occur via boiling histotripsy and/or cavitation histotripsy, among other techniques.
  • the first ultrasound waves may be applied using the ultrasound transducer 110, for example.
  • the first ultrasound waves may take the form of a beam that is selectively and/or sequentially focused upon the regions 312, 313, 314, 322, 323, and 324. In this context, the first ultrasound waves may be applied according to one or more first parameters.
  • the one or more first parameters of the first ultrasound waves may include any combination of one or more of: a sonication trajectory (e.g., path), a sequence upon which the first ultrasound waves are focused respectively upon each of the one or more target regions, a quantity of consecutive or non-consecutive pulses that may be focused respectively upon each of the one or more target regions, pulse durations, duty cycle, pulse repetition frequency, oscillation frequency, power level, or intensity.
  • the one or more first parameters may be indicated as part of the first input received via the user interface 106, but other examples are possible.
  • FIG. 5 depicts some example parameters that may define the first ultrasound waves (or the second ultrasound waves discussed below).
  • Ultrasound waves 500 may take the form of one or more pulses, such as pulses 502, 504, and 506.
  • Each of the pulses 502-506 may have an oscillation frequency f osc , pulse duration ti, pulse repetition frequency f 2 , and/or a duty cycle ti/t 2 as illustrated by Figure 5.
  • the pulses 502-506 may have a power level defined at least in part by an amplitude "A."
  • a power density level e.g., intensity, W/cm 2
  • defining the pulses 502-506 may also account for the spatial distribution of the ultrasound power embodied by the pulses 502-506 (e.g., beamwidth).
  • the method 200 involves, contemporaneous to or after applying the first ultrasound waves, acquiring second MRI data corresponding to the biological tissue.
  • the acquired second MRI data may reflect physical effect(s), if any, that the first ultrasound waves have upon the biological tissue 114.
  • Acquiring the second MRI data (or the first MRI data) may include any technique known in the art for using an MRI imaging system, the technique being suitable for acquiring the many forms MRI data may take as described above.
  • the method 200 involves determining, based on the second MRI data, one or more second parameters for applying second ultrasound waves to the biological tissue.
  • the second ultrasound waves might be applied immediately after the first ultrasounds waves, reflecting a real-time MRI feedback process.
  • fractionation of the one or more target regions may be proceeding as expected, and the one or more second parameters might be selected to be the same as the one or more first parameters. That is, it may be determined that no corrective action is required based on monitoring of the progress of the fractionation of the biological tissue 114 via the first ultrasound waves.
  • fractionation of the one or more target regions via the first ultrasound waves might not be proceeding as expected, and a suitable adjustment to the sonication trajectory or parameters may be in order.
  • the determined one or more second parameters may include parameters similar to any of the examples provided above for the one or more first parameters of the first ultrasound waves.
  • the one or more second parameters may be indicated by second input received via the user interface 106 (e.g., after viewing of the effects of the first ultrasound waves) and the processor may assign the one or more second parameters to the second ultrasound waves accordingly.
  • Figure 6 shows the user interface 106 displaying an image 380.
  • the image 380 may be a real-time MRI image of the biological tissue 114 as the ultrasound waves 500 are being applied to the target region 312 of the biological tissue 114.
  • the image 380 may be an image of the biological tissue 114 sometime after the first ultrasound waves have been applied to the biological tissue 114.
  • Figure 6 depicts the region 312 as being at least partially mechanically fractionated.
  • a user might view the image 380 and determine the one or more second parameters for upcoming sonication based on certain characteristics of the biological tissue 114 shown in the image 380. For instance, the user might decide that the first ultrasound waves fractionated the region 312 too quickly, and decide that the second ultrasound waves should be applied to the region 313 with a lower power setting than the first ultrasound waves. In another example, the user might determine that the focus of the first ultrasound waves is too wide and decide that the focus of the second ultrasound waves should be narrower than the first ultrasound waves.
  • the user might operate the ultrasound transducer 110 according to three criteria: (1) stopping or pausing sonication of the region 312 or refocusing ultrasound waves upon another target region of the treatment trajectory if an MRI signal intensity corresponding to the region 312 exceeds a threshold corresponding to a suitable degree of mechanical fractionation, (2) stopping or pausing sonication if a temperature indicated by the second MRI data indicates a temperature of the biological tissue 114 that exceeds a threshold temperature, and (3) stopping sonication of the biological tissue 114 as a whole if a maximum duration of sonication is exceeded.
  • sonication may proceed according to the one or more first parameters without adjustment.
  • the processor(s) 102 may automatically make such determinations and adjust the sonication protocol accordingly. That is, the one or more second parameters for the second ultrasound waves may be determined either automatically by the processor(s) 102 or manually via input received by the user interface 106.
  • Ultrasound parameters may be adjusted based on many other action criteria as well. Such parameters may include any combination of one or more of peak output power, peak acoustic pressure (e.g., either at the focus or at the transducer), oscillation frequency, duty cycle, pulse duration, pulse repetition rate, or trajectory. Other examples are possible.
  • the first input received by the user interface 106 may also indicate one or more characteristics of the second MRI data for evaluation.
  • the first input might indicate (1) MRI signal intensity of region 312 and (2) the temperature of the region 338 indicated by the second MRI data as criteria of the second MRI data to be evaluated.
  • the first input may further include commands to: (1) stop or pause sonication of the region 312 or refocus ultrasound waves upon another target region of the treatment trajectory if the MRI signal intensity corresponding to the region 312 exceeds a threshold corresponding to a suitable degree of mechanical fractionation, (2) stop or pause sonication if the temperature corresponding to target region 338 exceeds a threshold temperature, and (3) stopping sonication of the biological tissue 114 as a whole if a maximum duration of sonication is exceeded.
  • the processor(s) 102 may determine the one or more second parameters based on evaluating the characteristics of the second MRI data identified by the first input.
  • Such characteristics of the second MRI data may include signal intensity, proton signal intensity, Tl signal intensity, T2 signal intensity, indicated temperature, indicated tissue diffusivity, indicated tissue elasticity, or indicated tissue deformation.
  • the one or more second parameters may also be determined based on a total ultrasound exposure duration or a total sonication energy absorbed by the biological tissue.
  • the method 200 involves applying the second ultrasound waves to the biological tissue according to the one or more second parameters.
  • Block 212 may be similar to block 206 with the possible exception that the one or more second parameters might be different from the one or more first parameters as described above. In other examples, the one more first parameters might be equal to the one or more second parameters.
  • Figure 7 shows an image 390 of the biological tissue 114.
  • Avoidance regions 328, 329, 338, and 339 are shown in a shade of gray that is darker than that of the target regions 312, 313, 314, 322, 323, and 324.
  • the avoidance regions 328, 329, 338, and 339 may include tissues such as bone, muscle, skin, blood vessels, nerves, bowels, lungs, or other organs for which sonication is not intended and for which overheating or other damage is undesirable.
  • characteristics of a portion of the second MRI data corresponding to the avoidance regions 328, 329, 338, and 339 may be evaluated. This may involve characteristics such as signal intensity, proton signal intensity, Tl signal intensity, T2 signal intensity, indicated temperature, indicated tissue diffusivity, indicated tissue elasticity, or indicated tissue deformation.
  • the first input received by the user interface 106 may also indicate the avoidance regions 328, 329, 338, and 339 as regions to be monitored while the target regions 312, 313, 314, 322, 323 are sonicated.
  • the input identifying the avoidance regions may be similar to the input that indicates the target regions 312, 313, 314, 322, 323, and 324.
  • the first input may further indicate particular characteristics of the MRI data corresponding to the avoidance regions 328, 329, 338, and 339 to be evaluated.
  • the first input may further indicate that a signal intensity of the second MRI data corresponding to the avoidance region 338 should be monitored.
  • the processor may evaluate the MRI data corresponding to the avoidance region 338 in real-time, and may pause sonication or redirect the ultrasound beam if the signal intensity corresponding to the avoidance region 338 exceeds a threshold value.
  • the processor may evaluate the MRI data corresponding to the avoidance region 338 in real-time, and may pause sonication or redirect the beam (e.g., away from the avoidance region 338) if the temperature corresponding to the avoidance region 338 exceeds a threshold temperature (e.g., 43° C).
  • a threshold temperature e.g., 43° C
  • a user may use the MRI imaging system 116 to acquire MRI data corresponding to a biological tissue.
  • the user interface 106 may display an image representing the acquired MRI data.
  • the user may provide input via the user interface 106 indicating a two-dimensional or three-dimensional region of interest (ROI) of approximately 1 cm in diameter, centered on a target location.
  • the processor(s) 102 may generate (e.g., calculate) one or more treatment trajectories for boiling histotripsy within the ROI, with user-prescribed separation between the points and trajectories.
  • the user interface 106 might also receive input indicating two-dimensional ROIs in the near field, and in the far field, to indicate regions in which high temperature elevations should be avoided.
  • the processor(s) 102 may use these latter ROIs to define avoidance regions.
  • a sonication protocol may be determined such that if a Tl signal intensity of the ROI in the target region exceeds a threshold signal intensity, the ultrasound transducer 110 may halt sonication. In a similar fashion, if signals corresponding to temperatures that exceed a threshold are detected from the avoidance regions, the ultrasound transducer 110 may halt sonication. Lastly, the ultrasound transducer 110 may halt sonication if a total sonication duration exceeds a threshold duration.
  • Input received by the user interface 106 may define the threshold signal intensity, the threshold temperature, and/or the threshold duration discussed above. The input received via the user interface 106 may also define any other parameter that characterizes ultrasound waves to be generated during the sonication.
  • the processor(s) 102 receives MRI data acquired by the MRI imaging system 116.
  • the processor(s) 102 adjusts the parameters of the sonication based on the acquired MRI data and causes the ultrasound transducer 110 to sonicate the biological tissue 114 accordingly.
  • the processor(s) 102 may repeatedly use the acquired MRI data to compare the actual Tl signal intensity within the target region to the predetermined minimum Tl signal intensity.
  • the processor(s) 102 may also repeatedly use the acquired MRI data to compare the actual temperature of the avoidance region to the predetermined threshold temperature.
  • the processor(s) 102 may repeatedly modify the sonication protocol according to the criteria defined above.
  • Figures 8-14 illustrate experiments that were performed to demonstrate the functionality of the aforementioned methods, devices, and systems.
  • Figure 8A is a coronal cross-section of a portion of ex vivo bovine liver tissue.
  • Figure 8B is a sagittal cross-section of the same liver tissue that is depicted in Figure 8A.
  • the images of Figures 8A and 8B were used to plan an experimental protocol for sonicating the liver tissue.
  • the ultrasound beam generated by a transducer was steered from left to right with respect to Figure 8B.
  • the images of Figures 8A and 8B can be used for planning of a sonication therapy.
  • regions-of-interest (ROI) for feedback control can be defined both within the target region (depicted by rectangles and circles) and/or outside of the target region.
  • ROI regions-of-interest
  • an ROI within the target region can be used to stop therapy once the diameter of the lesion as seen in real time exceeds 1 cm.
  • an ROI in the near field can be used to pause therapy once the temperature within this ROI exceeds, e.g., 43C.
  • the volume of the ROIs in this example are ⁇ ⁇ lO x 15 mm.
  • Figure 9 is a real time temperature map in the coronal image plane during a BH- sonication of the ex vivo bovine liver tissue described above. Temperature at the target location as well as in surrounding regions can be monitored in real time. This information can be utilized in closed-loop or user adjustable feedback control to avoid off-target temperature elevations and to perform safer treatments, as well as to control temperatures at the target. Different temperature limits and actions can be applied to different regions within the image using ROIs, action criteria, and logical conditions (e.g., AND, NAND, OR, NOR, XOR, etc.).
  • logical conditions e.g., AND, NAND, OR, NOR, XOR, etc.
  • Figure 10 depicts temperatures at the target, calculated from the real time temperature maps during a BH-sonication within the ex vivo bovine liver. Curves show a maximum temperature, mean temperature in a 10 x 10 mm ROI centered on the target, and the standard deviations. Similar curves can be calculated from regions outside of the target. This information can be used in closed-loop or user-adjustable feedback control to change target location of an ultrasound beam or to adjust sonication parameters to regulate temperatures both within and outside of the target region. Different temperature limits and actions can be applied to different regions within the image using ROIs, action criteria, and logical conditions. In this example, sonication was switched to another location (layer) by an automatic feedback algorithm at 800 seconds when the mean temperature at the target reached 38 °C.
  • Figure 11 A shows real time fast-field-echo (FFE) magnitude images during a BH- sonication within the ex vivo bovine liver in the coronal imaging plane.
  • Figure 1 IB shows the same information in the sagittal imaging plane.
  • a transducer sonicates from left to right in the sagittal image.
  • BH-lesion formation (indicated by arrows), corresponding to the planned locations and feedback ROIs, can be visualized in real time in these FFE images.
  • This information can be utilized to control or limit off-target lesion formation to perform safer treatments, as well as to control the target region location, shape, size, and degree of homogenization or fractionation in real time.
  • Different limits of signal intensity or elasticity change can be applied to different regions within the image using ROIs, action criteria, and logical conditions, based on baseline MRI signal intensity or elasticity measurements.
  • Figures 12A ,12B, 12C, and 12D are real time FFE magnitude images captured during a BH-sonication of the ex vivo bovine liver.
  • the images represent the coronal imaging plane.
  • BH-lesion formations, corresponding to the target locations and feedback ROIs, can be visualized in real time in these FFE images.
  • Figure 12A shows the ex vivo liver tissue after one volumetric BH sonication.
  • Figure 12B shows the liver tissue after two volumetric BH sonications.
  • Figure 12C shows the liver tissue after three volumetric BH sonications.
  • Figure 12D shows the liver tissue after four volumetric BH sonications.
  • the BH lesions are clearly visible in real time MRI, and also persistent on MR images acquired post-sonication. This information is useful since feedback control can be performed not only based on the current target region that is being sonicated, but also on the previous targets and ROIs.
  • Figures 13A, 13B, and 13C are real time FFE magnitude images during a BH- sonication of the ex vivo bovine liver in the sagittal imaging plane. BH-lesion formations, corresponding to the planned locations and feedback ROIs, can be visualized in real time in these FFE images.
  • Figure 13 A shows the liver tissue after one volumetric BH sonication, but prior to starting a second volumetric BH sonication.
  • Figure 13B shows the liver tissue during a second volumetric BH sonication.
  • Figure 13C shows the liver tissue after completion of the second volumetric BH sonication.
  • the mean signal intensity (indicated by an arrow) wasn't yet at a level corresponding to the action criteria, and thus the sonication was continued according to an automatic feedback algorithm.
  • the sonication was stopped according to the feedback algorithm when the mean signal intensity within the ROI exceeded a threshold and thus the action criterion was fulfilled.
  • Figure 14 is a T2-weighted image captured after a BH-sonication of the ex vivo bovine liver tissue in the coronal imaging plane.
  • BH-lesion locations, shapes, and sizes, corresponding to the planned locations and feedback ROIs, can be visualized and measured post-therapy, even without using MRI contrast agents.
  • This information can be used to assess post-therapy outcomes and used in closed-loop or user-adjustable feedback control.
  • the information on lesion location, shape, size, and signal intensity when compared to neighboring tissue can be used to plan subsequent sonications aimed toward merging existing lesions into one contiguous lesion, re-treat a lesion, or to make a decision to treat other targets or to end treatment.
  • Different MR-imaging methods may be needed to provide adequate contrast for specific tissue types.

Landscapes

  • Health & Medical Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Engineering & Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Radiology & Medical Imaging (AREA)
  • High Energy & Nuclear Physics (AREA)
  • Public Health (AREA)
  • Biomedical Technology (AREA)
  • Veterinary Medicine (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Physics & Mathematics (AREA)
  • Condensed Matter Physics & Semiconductors (AREA)
  • Medical Informatics (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Biophysics (AREA)
  • Molecular Biology (AREA)
  • Surgery (AREA)
  • Pathology (AREA)
  • Signal Processing (AREA)
  • Vascular Medicine (AREA)
  • Pulmonology (AREA)
  • Theoretical Computer Science (AREA)
  • Cardiology (AREA)
  • Physiology (AREA)
  • Surgical Instruments (AREA)
  • Magnetic Resonance Imaging Apparatus (AREA)

Abstract

La présente invention concerne des modes de réalisation donnés à titre d'exemple de dispositifs, de systèmes et de procédés de fractionnement mécanique de tissus biologiques à l'aide d'un contrôle en retour de l'imagerie par résonance magnétique (IRM). Les exemples peuvent consister à afficher une image représentant les premières données d'IRM correspondant aux tissus biologiques, et à recevoir une entrée identifiant une ou plusieurs régions cibles des tissus biologiques à fractionner mécaniquement par l'intermédiaire d'une exposition à des premières ondes ultrasonores. Les exemples peuvent en outre consister à appliquer les premières ondes ultrasonores et, simultanément ou après l'application des premières ondes ultrasonores, à acquérir des secondes données d'IRM correspondant aux tissus biologiques. Les exemples peuvent également consister à déterminer, sur la base des secondes données d'IRM, un ou plusieurs seconds paramètres pour appliquer des secondes ondes ultrasonores aux tissus biologiques, et à appliquer les secondes ondes ultrasonores aux tissus biologiques selon le ou les seconds paramètres.
PCT/US2016/038052 2015-06-18 2016-06-17 Contrôle en retour à base d'irm d'un fractionnement mécanique à base d'ultrasons de tissus biologiques Ceased WO2016205627A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
US15/737,670 US11224356B2 (en) 2015-06-18 2016-06-17 MRI-feedback control of ultrasound based mechanical fractionation of biological tissue
US17/543,276 US12396653B2 (en) 2015-06-18 2021-12-06 MRI-based feedback control of ultrasound based mechanical fractionation of biological tissue

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US201562181448P 2015-06-18 2015-06-18
US62/181,448 2015-06-18

Related Child Applications (2)

Application Number Title Priority Date Filing Date
US15/737,670 A-371-Of-International US11224356B2 (en) 2015-06-18 2016-06-17 MRI-feedback control of ultrasound based mechanical fractionation of biological tissue
US17/543,276 Continuation US12396653B2 (en) 2015-06-18 2021-12-06 MRI-based feedback control of ultrasound based mechanical fractionation of biological tissue

Publications (1)

Publication Number Publication Date
WO2016205627A1 true WO2016205627A1 (fr) 2016-12-22

Family

ID=57546750

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2016/038052 Ceased WO2016205627A1 (fr) 2015-06-18 2016-06-17 Contrôle en retour à base d'irm d'un fractionnement mécanique à base d'ultrasons de tissus biologiques

Country Status (2)

Country Link
US (2) US11224356B2 (fr)
WO (1) WO2016205627A1 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117018483A (zh) * 2023-10-08 2023-11-10 北京小超科技有限公司 一种温度增强的微分多焦点超声空化装置

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN119069085A (zh) * 2017-04-18 2024-12-03 直观外科手术操作公司 用于规划程序的图形用户界面
JP7572063B2 (ja) * 2019-08-26 2024-10-23 国立研究開発法人科学技術振興機構 線維化測定装置、線維化測定方法および特性測定装置

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130102932A1 (en) * 2011-10-10 2013-04-25 Charles A. Cain Imaging Feedback of Histotripsy Treatments with Ultrasound Transient Elastography
US20140350439A1 (en) * 2013-05-23 2014-11-27 General Electric Company System and method for focusing of high intensity focused ultrasound based on magnetic resonance - acoustic radiation force imaging feedback

Family Cites Families (44)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1993016641A1 (fr) 1992-02-21 1993-09-02 Diasonics, Inc. Systeme endocavitaire a ultrasons pour la planification et le traitement d'une affection localisee par therapie a visualisation
JP3325300B2 (ja) 1992-02-28 2002-09-17 株式会社東芝 超音波治療装置
JP2002505596A (ja) 1997-05-23 2002-02-19 トランサージカル,インコーポレイテッド Mri誘導治療装置及び方法
US6542767B1 (en) * 1999-11-09 2003-04-01 Biotex, Inc. Method and system for controlling heat delivery to a target
WO2001050156A1 (fr) 1999-12-30 2001-07-12 Transurgical, Inc. Fonctionnement associe d'un appareil a irm et d'un equipement electronique
CA2484515A1 (fr) 2002-05-30 2003-12-11 University Of Washington Couplage a hydrogel solide pour l'imagerie et la therapie par ultrasons
US7377900B2 (en) 2003-06-02 2008-05-27 Insightec - Image Guided Treatment Ltd. Endo-cavity focused ultrasound transducer
US7246939B1 (en) * 2003-10-23 2007-07-24 Gultekin David H Measurement of thermal diffusivity, thermal conductivity, specific heat, specific absorption rate, thermal power, heat transfer coefficient, heat of reaction and membrane permeability by nuclear magnetic resonance
US20060122509A1 (en) 2004-11-24 2006-06-08 Liposonix, Inc. System and methods for destroying adipose tissue
CN101291629B (zh) 2005-10-19 2010-12-01 株式会社日立医药 超声波诊断装置
US8257338B2 (en) 2006-10-27 2012-09-04 Artenga, Inc. Medical microbubble generation
US20080146912A1 (en) 2006-12-18 2008-06-19 University Of Maryland, Baltimore Inter-communicator process for simultaneous mri thermography and radio frequency ablation
US20080221649A1 (en) 2007-03-09 2008-09-11 Agustina Echague Method of sequentially treating tissue
CN101687103B (zh) * 2007-06-12 2014-05-14 皇家飞利浦电子股份有限公司 一种用于图像引导治疗的系统
CA2706563C (fr) 2007-11-21 2018-08-21 Focus Surgery, Inc. Methode de diagnostic et de traitement de tumeurs par ultrasons focalises a haute intensite
CA2739425A1 (fr) 2008-10-03 2010-04-08 Mirabilis Medica, Inc. Methode et appareil permettant de traiter des tissus avec des ufhi
US8353832B2 (en) 2008-10-14 2013-01-15 Theraclion Systems and methods for ultrasound treatment of thyroid and parathyroid
US9101752B2 (en) 2008-11-17 2015-08-11 Sunnybrook Health Sciences Centre Computer controlled focused ultrasound positioning system for sequential beam emitting to sonicate discrete and interleaved tissue locations
WO2010077980A1 (fr) 2008-12-16 2010-07-08 Aardvark Medical, Inc. Procédés et systèmes d'administration de fluides, d'aérosols et d'énergie acoustique à des surfaces de tissu, des cavités et des passages obstrués tels que des ostiums intra-nasaux
US20100191157A1 (en) 2009-01-27 2010-07-29 Sanghvi Narendra T Method for treating skin lesions
WO2010118307A1 (fr) * 2009-04-09 2010-10-14 The Trustees Of The University Of Pennsylvania Procédés et systèmes pour un traitement de vaisseaux sanguins guidé par image
US20120035464A1 (en) * 2009-04-20 2012-02-09 Koninklijke Philips Electronics N.V. Control apparatus for controlling a therapeutic apparatus
CA2770700C (fr) 2009-08-26 2018-04-24 William W. Roberts Bras de commande de micromanipulateur pour transducteurs therapeutiques et d'imagerie du type a ultrasons
US8876740B2 (en) 2010-04-12 2014-11-04 University Of Washington Methods and systems for non-invasive treatment of tissue using high intensity focused ultrasound therapy
US9192790B2 (en) 2010-04-14 2015-11-24 Boston Scientific Scimed, Inc. Focused ultrasonic renal denervation
EP2423700A1 (fr) * 2010-08-30 2012-02-29 Koninklijke Philips Electronics N.V. Appareil, procédé informatique et produit de programme informatique pour calculer la température conformément aux données de relaxométrie transversale IRM
EP2489407A1 (fr) * 2011-02-15 2012-08-22 Koninklijke Philips Electronics N.V. Appareil thérapeutique de réchauffement d'un sujet
US9737353B2 (en) 2010-12-16 2017-08-22 Biosense Webster (Israel) Ltd. System for controlling tissue ablation using temperature sensors
KR101221824B1 (ko) * 2010-12-28 2013-03-05 알피니언메디칼시스템 주식회사 치료 장치 및 그 장치의 구동 방법
WO2012120495A2 (fr) 2011-03-04 2012-09-13 Rainbow Medical Ltd. Traitement et surveillance des tissus par application d'énergie
US9498651B2 (en) 2011-04-11 2016-11-22 University Of Washington Methods of soft tissue emulsification using a mechanism of ultrasonic atomization inside gas or vapor cavities and associated systems and devices
US20120302927A1 (en) 2011-05-23 2012-11-29 University Of Washington Methods for characterizing nonlinear fields of a high-intensity focused ultrasound source and associated systems and devices
US9028470B2 (en) * 2011-06-17 2015-05-12 University Of Utah Research Foundation Image-guided renal nerve ablation
US8583211B2 (en) 2011-08-10 2013-11-12 Siemens Aktiengesellschaft Method for temperature control in magnetic resonance-guided volumetric ultrasound therapy
US9392992B2 (en) 2012-02-28 2016-07-19 Siemens Medical Solutions Usa, Inc. High intensity focused ultrasound registration with imaging
JP5809770B2 (ja) 2012-04-12 2015-11-11 コーニンクレッカ フィリップス エヌ ヴェKoninklijke Philips N.V. 電子焦点区域よりも大きい標的区域を加熱するための高密度焦点式超音波
US10441769B2 (en) * 2012-05-04 2019-10-15 University Of Houston Targeted delivery of active agents using thermally stimulated large increase of perfusion by high intensity focused ultrasound
US20130345552A1 (en) 2012-06-26 2013-12-26 Covidien Lp Methods and systems for enhancing ultrasonic visibility of energy-delivery devices within tissue
US9427161B2 (en) * 2012-07-23 2016-08-30 Northwestern University Curved passive acoustic driver for magnetic resonance elastography
CN105682739B (zh) * 2013-01-29 2018-11-13 因赛泰克有限公司 基于模拟的聚焦超声治疗计划
WO2014164363A1 (fr) 2013-03-09 2014-10-09 Kona Medical, Inc. Transducteurs, systèmes et techniques de fabrication pour thérapies à ultrasons focalisés
KR20140113172A (ko) 2013-03-15 2014-09-24 삼성전자주식회사 초음파 조사 계획 수립 방법 및 장치, 초음파 조사 방법
US20140330175A1 (en) 2013-05-03 2014-11-06 SonaCare Medical, LLC System and method for coupling and depth control for ultrasound
US10694974B2 (en) 2014-03-27 2020-06-30 University Of Washington Method and system for MRI-based targeting, monitoring, and quantification of thermal and mechanical bioeffects in tissue induced by high intensity focused ultrasound

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130102932A1 (en) * 2011-10-10 2013-04-25 Charles A. Cain Imaging Feedback of Histotripsy Treatments with Ultrasound Transient Elastography
US20140350439A1 (en) * 2013-05-23 2014-11-27 General Electric Company System and method for focusing of high intensity focused ultrasound based on magnetic resonance - acoustic radiation force imaging feedback

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
BEBBINGTON, M ET AL.: "Comparison of ultrasound and magnetic resonance imaging parameters in predicting survival in isolated left-sided congenital diaphragmatic hernia.", ULTRASOUND IN OBSTETRICS & GYNECOLOGY, vol. 43, no. 6, 2014, pages 670 - 674, XP055339306 *
VLAISAVLJEVICH, E ET AL.: "Image-guided non-invasive ultrasound liver ablation using histotripsy: Feasibility study in an in vivo porcine model.", ULTRASOUND IN MEDICINE & BIOLOGY, vol. 39, no. 8, 2013, pages 1398 - 1409, XP055339303 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117018483A (zh) * 2023-10-08 2023-11-10 北京小超科技有限公司 一种温度增强的微分多焦点超声空化装置
CN117018483B (zh) * 2023-10-08 2023-12-22 北京小超科技有限公司 一种温度增强的微分多焦点超声空化装置

Also Published As

Publication number Publication date
US12396653B2 (en) 2025-08-26
US20220304588A1 (en) 2022-09-29
US11224356B2 (en) 2022-01-18
US20200037916A1 (en) 2020-02-06

Similar Documents

Publication Publication Date Title
US10694974B2 (en) Method and system for MRI-based targeting, monitoring, and quantification of thermal and mechanical bioeffects in tissue induced by high intensity focused ultrasound
US12157018B2 (en) Boiling histotripsy methods and systems for uniform volumetric ablation of an object by high-intensity focused ultrasound waves with shocks
RU2707037C2 (ru) Система и способ адаптивной абляции и терапии на основании эластографического мониторинга
US12396653B2 (en) MRI-based feedback control of ultrasound based mechanical fractionation of biological tissue
EP2519324B1 (fr) Appareil thérapeutique
US9028470B2 (en) Image-guided renal nerve ablation
US10271890B2 (en) High intensity focused ultrasound enhanced by cavitation
CN102802728A (zh) Mr成像引导的治疗
EP2636368A1 (fr) Modification d'un plan de traitement utilisant des données de résonance magnétique acquises pendant une période de refroidissement
Zhou Generation of uniform lesions in high intensity focused ultrasound ablation
JPH0747079A (ja) 超音波治療装置
KR102320038B1 (ko) 가변음압 집속초음파를 이용한 생체조직 정밀 제거 장치 및 방법
RU2608433C2 (ru) Устройство, выполняющее тестовые обработки ультразвуком с использованием высокоинтенсивного фокусированного ультразвука
EP3274049B1 (fr) Instrument médical destiné à la sonication d'un ensemble de volumes cibles
JP6599885B2 (ja) 正規化された変位差に基づく熱的破壊痕サイズ制御のための手法
RU2666986C2 (ru) Система терапии для подвода энергии
CN112384279B (zh) 治疗规划设备
Elbes et al. Magnetic resonance imaging for the exploitation of bubble-enhanced heating by high-intensity focused ultrasound: a feasibility study in ex vivo liver
JP2017524412A (ja) 熱焼灼システム及びその方法
CN109009430B (zh) 治疗辅助装置以及治疗辅助方法
EP3459596A1 (fr) Réglage de puissance dans des ultrasons focalisés de haute intensité guidés par résonance magnétique
Partanen et al. Use of MRI to visualize mechanically fractionated lesions generated by boiling histotripsy in tissue Abstract
McDannold et al. MRI-based thermometry and thermal dosimetry during focused ultrasound thermal ablation of uterine leiomyomas
Hynynen et al. MRI-Guided Focused Ultrasound Treatment of the Brain
Hey et al. Adaptive volumetric MR‐guided high‐intensity focused ultrasound ablations for moving organs

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 16812510

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 16812510

Country of ref document: EP

Kind code of ref document: A1